Large scale service providers providing data, content and applications via the Internet look to maximize availability and responsiveness of clustered server systems. They also seek to maintain minimal total costs of ownership for their systems. As more users access such information, demand for faster delivery and responsiveness increases.
Delivery systems have been developed whereby geographically dispersed networks of edge locations can each store copies of content. Each edge location can include one or multiple servers. Clients requesting the content are routed to the nearest edge location so the content is delivered with the best possible performance. To achieve the best possible performance, the edge locations are typically high performance data centers that are able to respond to requested loads during peak times.
The primary issue with this strategy is that the edge locations or “caches” need to manage freshness or validity of their content. Edge locations expire the content and refresh it on a relatively frequent basis. The requirement for freshness creates cache misses which may end up invoking back end services at a higher cost. In some cases the content has expired based on a time-to-live (TTL) value, but the content may not actually have changed. In many systems, there is no mechanism to refresh the edge cache without executing the full heavyweight retrieval from the back end service. This results in a large amount of network traffic and back end service calls which yield no benefit to the service provider or end user. In current multi-tier cache systems, it may be difficult to ensure content freshness without forcing every caching layer have shorter than desired TTL values. The cost of a refresh includes the cost of a proxy cache miss at every cache layer and back end server processing.